Human beings are sometimes used as subjects in different types of medical, psychological, and other research. Generally, such research fits into one of several broad categories: academic or industrial research, FDA clinical trials, and marketing and sales research. Human beings are also used as research subjects in experiments designed to correlate genotype and phenotype with drug reactions. For example, a researcher may seek to learn whether patients with the genotype for sickle cell disorder experience greater light sensitivity when taking a specific antibiotic.
Academic and industrial investigators often employ human subjects to learn how humans respond to some pre-determined stimuli such as a drug or a psychological event. For a first example, an academic researcher may use post-menopausal women as subjects in experiments designed to widen our understanding of the neuroendocrine response to ethanol. Many different types of data can be obtained in such experiments. In this first example, a researcher could correlate the data on different hormone levels with blood alcohol levels, the frequency of selected patient behaviors, number of cigarettes smoked and many other possible factors. These data can be aggregated with similar data from other researchers and conclusions can be drawn based upon their observations.
A second area in which human subjects are sometimes used as a research tool involves government approval of new drugs for human patients. The Food and Drug Administration (FDA) approves new drugs that are to be marketed for human consumption. Presently, FDA approval is contingent upon the drug successfully passing three phases of testing during which the drug is blindly administered to human subjects. Taken together, these three phases of testing are called clinical trials. Only those drugs that successfully complete all three phases of clinical trials can be marketed.
In the general course of events, the sponsor of a drug will submit an application and protocol to the FDA for clinical testing. After the application is reviewed and approved, Phase I of clinical testing begins. Experienced clinical investigators administer the drug to a small number of healthy volunteers. Although drug dosage and metabolism may be studied, the main focus of this initial testing phase is drug safety. Since safety concerns are paramount, testing is performed on a relatively small population (between 20 to 100 subjects) for a short period of time. Drugs that induce toxic reactions or other adverse effects do not advance to Phase II. This initial screening eliminates approximately 30% of all applicants.
The main focus of Phase II testing is to determine whether the drug is an effective treatment. Since the focus is on the effectiveness of the drug and the threat of adverse reactions has been largely ruled out, Phase II clinical trials involve a larger number of subjects (up to several hundred) who suffer from a problem the drug is designed to treat. Phase II trials may involve the blind testing of up to several hundred subjects. Only 33% of all drugs advance to phase III testing.
Phase III testing may involve up to several thousand subjects. This phase lasts longer (between one to four years) than either Phase I or Phase II. Here, the safety, dosage and effectiveness of the new drug are all rigorously screened. Between 25-30% of all drugs pass phase III trials and receive the required approval necessary for marketing.
An additional level of testing is also employed. After a new drug has passed all three phases of clinical trials, researchers may also want to learn if any adverse effects occur after the drug is marketed. Thus, additional investigation may involve post-marketing surveillance of patients who have been administered the drug after it is approved by the FDA. Such post marketing surveillance is a useful tool that helps researchers learn more about how patients respond to a specific drug.
Known marketing and sales research includes attempting to elicit responses from human participants regarding whether those participants would be more or less likely to purchase selected goods or services. It is known to attempt to correlate responses with demographic data about the participants (such as age, gender, household income, or residence locale), as well as psychological and other information about participants (such as whether participants are considered ““early adopters”).
Known methods for collecting and analyzing data from human subjects in research suffer from several drawbacks. While these methods generally achieve their respective goals of learning more about the human response to various stimuli, screening out ineffective and unnecessarily toxic drugs, and providing useful information for marketing or sales, known methods suffer from several drawbacks and limitations that can make them time-consuming or inefficient.
A first problem in the known art is that collection of data from subjects or participants in research or clinical trials often involves obtaining and analyzing fuzzy assessments from subjects who are not necessarily under the continual observation of a clinician or other personnel. Indeed, many subjects (such as the controls in clinical trials) are not under the care of a physician at all, but merely report to an expert researcher periodically for testing and analysis. Such testing and analysis frequently involves self-reporting a number of parameters. A subject's answer to an inquiry often involves the making of a fuzzy assessment of physical state, mood or quality of life. Accordingly, there is a need for a method to evaluate and standardize such fuzzy self-assessments.
A second problem in the known art is that researchers are unable to respond to incoming data in real time. In known methods, data from research or clinical trials is collected and stored for analysis at a later time. Frequently, researchers or lab technicians enter their observations in a paper copy of a log book or lab notebook. Often these results are entered near the end of an experiment. This practice makes it impossible for an investigator to evaluate the data or change the experimental design. While researchers may have an approximate idea as to the general trend of incoming data, they are frequently unable to respond to that trend until the data is analyzed, well after any opportunity for altering the method of collection or the nature of the data collected. Accordingly, researchers are unable to modify a clinical protocol while in process. This inability to evaluate and respond to incoming data during data collection can create conditions that are dangerous for the subjects of the research. It is believed that morbidity and mortality associated with evaluation of new drugs would be substantially reduced if researchers could respond during the research, such as to halt the clinical trial or adjust the drug dosage. Accordingly, there is a need to evaluate and respond to subjects in real time.
A third problem in the known art is that collection of data from research and clinical trials often calls for the aggregation of data from many different geographical testing sites. It is believed that drug testing and other research would be quicker if there were a way to aggregate data and respond to it in real time, during the time of the trials or research. Accordingly, there is a need to aggregate and analyze data from many remote sites.
A fourth problem in the known art is that identification of subjects in clinical trials who respond to a drug is not always readily apparent because it frequently requires evaluation of many different parameters. Part of this problem involves the nature of disease. In some cases, an acute condition will spontaneously heal, regardless of treatment. Chronic diseases often follow an unpredictable course as symptoms abate for a time and then worsen. Under these conditions, it is often difficult to determine whether the change in the subject's condition may be attributed to the drug or some other factor. Identifying subjects who respond to a drug is particularly problematic in Phase II trials where the issue is the efficacy of the drug. Accordingly, there is a need to be able to distinguish responders from non-responders on the basis of many different factors.
A fifth problem in the known art involves the nature of research with human subjects. Most experiments involving administration of drugs are either blinded or double blinded. In blinded studies, the subject does not know whether they are receiving the active drug or a placebo. In essence, although the investigator knows what the subject is receiving, the subject does not know whether or not they are being used as a control. In double-blinded subjects, neither the researcher nor the research subject is aware of the subject's status. Blinded studies are problematic because researcher may impose his own bias on the incoming data. Double-blinded studies are problematic because the researcher may not be sensitive to phenomena that the subject is experiencing. Another problem raised in double-blinded studies is that the investigator very often becomes unblinded when observing the effect of a drug on a research subject. According, there is a need for an impartial, unbiased observer that remains responsive to the research subjects.
Accordingly, it would be advantageous to provide a technique by which research data can be collected and analyzed during the course of the research testing, and the research testing itself possibly modified to account for conclusions drawn from the research data. For example, it would be advantageous to provide a device that can be carried by a research subject or participant that can be coupled and uncoupled to a communication system that is also accessible to researchers and other remote experts. Such a device would allow researchers to (1) collect, analyze and respond to input from the research subjects or participants in real time, (2) evaluate fuzzy assessments made by a subject or participant by making progressively narrower inquiries designed to obtain specific data, (3) aggregate and analyze data from a large number of remote sites quickly, (4) change the research protocol in response to input from subjects in real time and (5) rapidly identify responders and non-responders by correlating the data with a number of disparate parameters that are not necessarily apparent when the study begins. These advantages are achieved in embodiments of the invention in which a research subject enters data using a client device that is coupled to a server via a communication link.